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Hierarchy of Evidence: A Simple System for Orthopaedic Research?

2007· article· en· W2078107425 on OpenAlexaff
Julia Pemberton, Juliana Kraeva, Mohit Bhandari

Bibliographic record

VenueJournal of Long-Term Effects of Medical Implants · 2007
Typearticle
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsHamilton General HospitalMcMaster University
Fundersnot available
KeywordsCategorizationHierarchyComputer scienceRating systemSimple (philosophy)Quality (philosophy)Expert opinionEvidence-based medicineBest evidenceExpert systemData scienceQuality of evidenceManagement sciencePsychologyKnowledge managementMedicineMedical educationAlternative medicineArtificial intelligenceEngineeringMeta-analysisPathology

Abstract

fetched live from OpenAlex

To be able to make a sound recommendation for a treatment based on the best available evidence, it is necessary to follow specific steps in acquiring literature, appraising the study design and quality, and assessing the results. Evidence-based medicine is founded on the concepts of using best evidence, levels of evidence, and grades of recommendation, and aims to provide clinicians with standardized rules to help them appraise the validity of published research. A number of systems have been developed to categorize research studies into consistent levels of evidence. These systems are based primarily on consensus expert opinion, and have not been validated to any extent. The use of different systems does not allow for effective communication between users; there is a lack of accord even between users of the same system. The GRADE working group has devised a new rating system that attempts to address deficiencies seen within other systems.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.408
metaresearch head score (Gemma)0.256
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.524
Threshold uncertainty score0.799

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.4080.256
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0040.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.777
GPT teacher head0.624
Teacher spread0.153 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2007
Admission routes1
Has abstractyes

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